Comparison of energy expenditure estimates from 4 physical activity questionnaires with doubly labeled water estimates in postmenopausal women

Physical activity and fertility in women: the North-Trøndelag Health Study

BACKGROUND

Changes in the state of energy balance owing to changes in physical activity may affect the reproductive system. We evaluated the association between physical activity (PA) and fertility and parity in healthy women.

METHODS

A population-based health survey (HUNT 1) was conducted during 1984-1986 in Nord-Trøndelag county, Norway, with follow-up from 1995 to 1997 (HUNT 2). The study included 3887 women, <45 years old in HUNT 2. PA was assessed by baseline questionnaire, and fertility and parity by questionnaire at follow-up. Data focused on overall occurrence of infertility in the population (without biological confirmation).

RESULTS

Increased frequency, duration and intensity of PA were associated with increased subfertility, and frequency of PA was associated with voluntary childlessness (P < 0.01). After adjusting for age, parity, smoking, and marital status, women who were active on most days were 3.2 times more likely to have fertility problems than inactive women. Exercising to exhaustion was associated with 2.3 times the odds of fertility problems versus low intensity. Women with highest intensity of PA at baseline had the lowest frequency of continuing nulliparity and highest frequency of having three or more children during follow-up (P < 0.05). Sensitivity analysis including body mass index as confounder did not alter the results. No associations were found between lower activity levels and fertility or parity.

CONCLUSION

Increased risk of infertility was only found for the small group of women reporting the highest levels of intensity and frequency of PA. Awareness of the possible risks of infertility should be highlighted among non-athletic women who exercise vigorously.

Is it possible to assess free-living physical activity and energy expenditure in young people by self-report?

BACKGROUND

It is unclear whether it is possible to accurately estimate physical activity energy expenditure (PAEE) by self-report in youth.

OBJECTIVE

We assessed the validity and reliability of 4 self-reports to assess PAEE and time spent at moderate and vigorous intensity physical activity (MVPA) over the previous week in British young people between 4 and 17 y of age.

DESIGN

PAEE and MVPA were derived from the Children's Physical Activity Questionnaire, Youth Physical Activity Questionnaire, and Swedish Adolescent Physical Activity Questionnaire; a lifestyle score indicative of habitual activity was derived from the Child Heart and Health Study in England Questionnaire. These data were compared with criterion methods, PAEE, and MVPA derived from simultaneous measurements by doubly labeled water and accelerometry in 3 age groups: 4-5 y (n = 27), 12-13 y (n = 25), and 16-17 y (n = 24). Validity was assessed by using Spearman correlations and the Bland-Altman method, and reliability was assessed by using intraclass correlation coefficients.

RESULTS

The strength of association between questionnaire and criterion methods varied (r = 0.09 to r = 0.46). Some questionnaires were able to accurately assess group-level PAEE and MVPA for some age groups, but the error was large for individual-level estimates throughout. Reliability of the Youth Physical Activity Questionnaire and Child Heart and Health Study in England Questionnaire was good (intraclass correlation coefficient: 0.64-0.92).

CONCLUSIONS

Absolute PAEE and MVPA estimated from these self-reports were not valid on an individual level in young people, although some questionnaires appeared to rank individuals accurately. Age (the outcome of interest) and whether individual or group-level estimates are necessary will influence the best choice of self-report method when assessing physical activity in youth.

Assessment of physical activity: a critical appraisal

Assessment of physical activity in a free-living environment is important for understanding relations between physical activity and health and determining the effectiveness of interventions. Techniques include behavioral observation, questionnaires in the form of diaries, recall questionnaires and interviews, and physiological markers like heart rate, calorimetry, and motion sensors. The doubly labeled water method has become the gold standard for the validation of field methods of assessing physical activity. Then, questionnaires show a low reliability and validity but can be adequately applied as an activity-ranking instrument. The heart rate requires individual calibration to be an effective method to assess physical activity only at group level. The indicated method for the assessment of habitual physical activity in daily life is a doubly labeled water validated accelerometer. Future developments are simultaneous measurement of body acceleration and heart rate for the assessment of physical fitness. A new generation of accelerometers will provide information on body posture and activity recognition to allow objective assessment of subjects' habitual activities, options for a healthy change, and effects of the follow-up of any changes.

The work and home activities questionnaire: energy expenditure estimates and association with percent body fat

BACKGROUND

Understanding and increasing physical activity requires assessment of occupational, home, leisure and sedentary activities.

METHODS

A physical activity questionnaire was developed using data from a large representative U.S. sample; includes occupational, leisure and home-based domains; and produces estimates of energy expenditure, percent body fat, minutes in various domains, and meeting recommendations. It was tested in 396 persons, mean age 44 years. Estimates were evaluated in relation to percent body fat measured by dual-energy x-ray absorptiometry.

RESULTS

Median energy expenditure was 2365 kcal (women) and 2960 kcal (men). Women spent 35.1 minutes/day in moderate household activities, 13.0 minutes in moderate leisure and 4.0 minutes in vigorous activities. Men spent 18.0, 22.5 and 15.6 minutes/day in those activities, respectively. Men and women spent 276.4 and 257.0 minutes/day in sedentary activities. Respondents who met recommendations through vigorous activities had significantly lower percent body fat than those who did not, while meeting recommendations only through moderate activities was not associated with percent body fat. Predicted and observed percent body fat correlated at r = .73 and r = .82 for men and women respectively, P < .0001.

CONCLUSIONS

This questionnaire may be useful for understanding health effects of different components of activity, and for interventions to increase activity levels.

A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review

BACKGROUND

Accurate assessment is required to assess current and changing physical activity levels, and to evaluate the effectiveness of interventions designed to increase activity levels. This study systematically reviewed the literature to determine the extent of agreement between subjectively (self-report e.g. questionnaire, diary) and objectively (directly measured; e.g. accelerometry, doubly labeled water) assessed physical activity in adults.

METHODS

Eight electronic databases were searched to identify observational and experimental studies of adult populations. Searching identified 4,463 potential articles. Initial screening found that 293 examined the relationship between self-reported and directly measured physical activity and met the eligibility criteria. Data abstraction was completed for 187 articles, which described comparable data and/or comparisons, while 76 articles lacked comparable data or comparisons, and a further 30 did not meet the review's eligibility requirements. A risk of bias assessment was conducted for all articles from which data was abstracted.

RESULTS

Correlations between self-report and direct measures were generally low-to-moderate and ranged from -0.71 to 0.96. No clear pattern emerged for the mean differences between self-report and direct measures of physical activity. Trends differed by measure of physical activity employed, level of physical activity measured, and the gender of participants. Results of the risk of bias assessment indicated that 38% of the studies had lower quality scores.

CONCLUSION

The findings suggest that the measurement method may have a significant impact on the observed levels of physical activity. Self-report measures of physical activity were both higher and lower than directly measured levels of physical activity, which poses a problem for both reliance on self-report measures and for attempts to correct for self-report - direct measure differences. This review reveals the need for valid, accurate and reliable measures of physical activity in evaluating current and changing physical activity levels, physical activity interventions, and the relationships between physical activity and health outcomes.

Estimates of adherence and error analysis of physical activity data collected via accelerometry in a large study of free-living adults

Background

Activity monitors (AM) are small, electronic devices used to quantify the amount and intensity of physical activity (PA). Unfortunately, it has been demonstrated that data loss that occurs when AMs are not worn by subjects (removals during sleeping and waking hours) tend to result in biased estimates of PA and total energy expenditure (TEE). No study has reported the degree of data loss in a large study of adults, and/or the degree to which the estimates of PA and TEE are affected. Also, no study in adults has proposed a methodology to minimize the effects of AM removals.

Methods

Adherence estimates were generated from a pool of 524 women and men that wore AMs for 13 – 15 consecutive days. To simulate the effect of data loss due to AM removal, a reference dataset was first compiled from a subset consisting of 35 highly adherent subjects (24 HR; minimum of 20 hrs/day for seven consecutive days). AM removals were then simulated during sleep and between one and ten waking hours using this 24 HR dataset. Differences in the mean values for PA and TEE between the 24 HR reference dataset and the different simulations were compared using paired t-tests and/or coefficients of variation.

Results

The estimated average adherence of the pool of 524 subjects was 15.8 ± 3.4 hrs/day for approximately 11.7 ± 2.0 days. Simulated data loss due to AM removals during sleeping hours in the 24 HR database (n = 35), resulted in biased estimates of PA (p < 0.05), but not TEE. Losing as little as one hour of data from the 24 HR dataset during waking hours results in significant biases (p < 0.0001) and variability (coefficients of variation between 7 and 21%) in the estimates of PA. Inserting a constant value for sleep and imputing estimates for missing data during waking hours significantly improved the estimates of PA.

Conclusion

Although estimated adherence was good, measurements of PA can be improved by relatively simple imputation of missing AM data.

Validity of the modified Baecke questionnaire: comparison with energy expenditure according to the doubly labeled water method

Background

In epidemiological research, physical activity is usually assessed by questionnaires. Questionnaires are suitable for large study populations since they are relatively inexpensive and not very time consuming. However, questionnaire information is by definition subjective and prone to recall bias, especially among elderly subjects. The Modified Baecke Questionnaire, developed by Voorrips and coworkers, measures habitual physical activity in the elderly. The questionnaire includes questions on household activities, sports, and leisure time activities, over a time period of one year. The Modified Baecke Questionnaire results in a score to classify people as high, moderate, or low in daily physical activity, based on tertiles.

Methods

The validity of the Modified Baecke Questionnaire score was assessed among 21 elderly men and women using the doubly labeled water method as the reference criterion. This method is considered to be the gold standard for measuring energy expenditure in free-living individuals. Energy expenditure on physical activity is estimated by the ratio of total energy expenditure measured by the doubly labeled water method and resting metabolic rate measured by indirect calorimetry. This ratio is called the physical activity ratio.

Results

The Spearman correlation coefficient between the questionnaire score and the physical activity ratio (PAR) was 0.54 (95% CI 0.22–0.66). Correct classification by the questionnaire occurred in 71% of participants who were in the lowest tertile of PAR, in 14% of participants in the middle tertile, and in 43% of participants in the highest tertile. Subjects were not wrongly classified in an opposite tertile.

Conclusion

The validity of the Modified Baecke Questionnaire is fair-to-moderate. This study shows that the questionnaire can correctly classify individuals as low or high active, but does a poor job for moderately active individuals.

Relationship between the metabolic syndrome and physical activity energy expenditure: a MONET study

The purpose of this cross-sectional study was to examine the association between the metabolic syndrome (MetS) and physical activity energy expenditure (PAEE) in overweight and obese sedentary postmenopausal women. The study population consisted of 137 overweight and obese sedentary postmenopausal women (age, 57.7 ± 4.8 years; BMI, 32.4 ± 4.6 kg·m–2). Subjects had the MetS if 3 out of the following 5 criteria were met: visceral fat > 130 cm2, high-density lipoprotein (HDL) cholesterol < 1.29 mmol·L–1, fasting triglycerides ≥ 1.7 mmol·L–1, blood pressure ≥ 130/85 mmHg, and fasting glucose ≥5.6 mmol·L–1. We measured (i) body composition (by dual-energy X-ray absorptiometry); (ii) visceral fat (by computed tomography); (iii) insulin sensitivity (using the hyperinsulinemic-euglycemic clamp); (iv) plasma lipids, fasting glucose, and insulin, as well as 2 h glucose during an oral glucose tolerance test; (v) resting blood pressure; (vi) peak oxygen consumption (VO2 peak); (vii) PAEE (using doubly labeled water); and (viii) lower-body muscle strength (using weight-training equipment). Forty-two women (30.7%) had the MetS in our cohort. Individuals without the MetS had significantly higher levels of PAEE (962 ± 296 vs. 837 ± 271 kcal·d–1; p < 0.05), VO2 peak (18.2 ± 3.0 vs. 16.7 ± 3.2 mL·min–1·kg–1; p < 0.05), and insulin sensitivity, as well as significantly lower levels of 2 h glucose and central lean body mass. No differences in total energy expenditure, resting metabolic rate, and muscle strength between groups were observed. Logistic regression analysis showed that 2 h glucose (odds ratio (OR): 1.50 (95% CI 1.17–1.92)), central lean body mass (OR: 1.17 (95% CI 1.05–1.31)), and PAEE (OR: 0.998 (95% CI 0.997–1.000)), but not VO2 peak and (or) muscle strength, were independent predictors of the MetS. Lower levels of PAEE and higher levels of 2 h glucose, as well as central lean body mass, are independent determinants of the MetS in our cohort of overweight and obese postmenopausal women.

Estimating activity energy expenditure: how valid are physical activity questionnaires?

Activity energy expenditure (AEE) is the modifiable component of total energy expenditure (TEE) derived from all activities, both volitional and nonvolitional. Because AEE may affect health, there is interest in its estimation in free-living people. Physical activity questionnaires (PAQs) could be a feasible approach to AEE estimation in large populations, but it is unclear whether or not any PAQ is valid for this purpose. Our aim was to explore the validity of existing PAQs for estimating usual AEE in adults, using doubly labeled water (DLW) as a criterion measure. We reviewed 20 publications that described PAQ-to-DLW comparisons, summarized study design factors, and appraised criterion validity using mean differences (AEE(PAQ) - AEE(DLW), or TEE(PAQ) - TEE(DLW)), 95% limits of agreement, and correlation coefficients (AEE(PAQ) versus AEE(DLW) or TEE(PAQ) versus TEE(DLW)). Only 2 of 23 PAQs assessed most types of activity over the past year and indicated acceptable criterion validity, with mean differences (TEE(PAQ) - TEE(DLW)) of 10% and 2% and correlation coefficients of 0.62 and 0.63, respectively. At the group level, neither overreporting nor underreporting was more prevalent across studies. We speculate that, aside from reporting error, discrepancies between PAQ and DLW estimates may be partly attributable to 1) PAQs not including key activities related to AEE, 2) PAQs and DLW ascertaining different time periods, or 3) inaccurate assignment of metabolic equivalents to self-reported activities. Small sample sizes, use of correlation coefficients, and limited information on individual validity were problematic. Future research should address these issues to clarify the true validity of PAQs for estimating AEE.

Measuring physical activity in older adults: use of the Community Health Activities Model Program for Seniors Physical Activity Questionnaire and the Yale Physical Activity Survey in three behavior change consortium studies

The purpose of this study was to use data from three Behavior Change Consortium intervention studies to consider the practicality of use of two surveys of physical activity (PA) relevant for older adults, provide support for the validity of these surveys, and provide guidance to researchers for decisions on use of one survey as opposed to the other. The samples included 218 participants in the Community Health Advice by Telephone Study, 150 participants in the Study of Exercise and Nutrition in Older Rhode Islanders, and 150 participants from the Testing the Effectiveness of the Exercise Plus Program. PA surveys included the Yale PA Survey and the Community Health Activities Model Program for Seniors PA Questionnaire. Older adults were able to complete either survey, although for frailer participants, an interview format is recommended. The Community Health Activities Model Program for Seniors PA Questionnaire was more likely to elicit information about moderate-intensity physical activities and was more likely to be related to vitality. Conversely, the Yale PA Survey may more comprehensively describe overall PA and provide information about moderate-intensity physical activity.

International Physical Activity Questionnaire (IPAQ) and New Zealand Physical Activity Questionnaire (NZPAQ): a doubly labelled water validation

BACKGROUND

Accurate measurement of physical activity is a pre-requisite for monitoring population health and for evaluating effective interventions. The International Physical Activity Questionnaire (IPAQ) is used as a comparable and standardised self-report measure of habitual physical activity of populations from different countries and socio-cultural contexts. The IPAQ has been modified to produce a New Zealand physical activity questionnaire (NZPAQ). The aim of this study was to validate the IPAQ and NZPAQ against doubly labelled water (DLW).

METHOD

Total energy expenditure (TEE) was measured over a 15-day period using DLW. Activity-related energy expenditure (AEE) was estimated by subtracting the energy expenditure from resting metabolic rate and thermic effect of feeding from TEE. The IPAQ (long form) and NZPAQ (short form) were completed at the end of each 7-day period. Activity-related energy expenditure (IPAQAEE and NZPAQAEE) was calculated from each questionnaire and compared to DLWAEE.

RESULTS

Thirty six adults aged 18 to 56 years (56% female) completed all measurements. Compared to DLWAEE, IPAQAEE and NZPAQAEE on average underestimated energy expenditure by 27% and 59%, respectively. There was good agreement between DLWAEE and both IPAQAEE and NZPAQAEE at lower levels of physical activity. However there was marked underestimation of questionnaire-derived energy expenditure at higher levels of activity.

CONCLUSION

Both the IPAQ and NZPAQ instruments have a demonstrated systematic bias toward underestimation of physical activity-related energy expenditure at higher levels of physical activity compared to DLW. Appropriate calibration factors could be used to correct for measurement error in physical activity questionnaires and hence improve estimation of AEE.

Comparison of two different physical activity monitors

Background

Understanding the relationships between physical activity (PA) and disease has become a major area of research interest. Activity monitors, devices that quantify free-living PA for prolonged periods of time (days or weeks), are increasingly being used to estimate PA. A range of different activity monitors brands are available for investigators to use, but little is known about how they respond to different levels of PA in the field, nor if data conversion between brands is possible.

Methods

56 women and men were fitted with two different activity monitors, the Actigraph™ (Actigraph LLC; AGR) and the Actical™ (Mini-Mitter Co.; MM) for 15 days. Both activity monitors were fixed to an elasticized belt worn over the hip, with the anterior and posterior position of the activity monitors randomized. Differences between activity monitors and the validity of brand inter-conversion were measured by t-tests, Pearson correlations, Bland-Altman plots, and coefficients of variation (CV).

Results

The AGR detected a significantly greater amount of daily PA (216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min, P < 0.0001). The average difference between activity monitors expressed as a CV were 3.1 and 15.5% for log-transformed and raw data, respectively. When a conversion equation was applied to convert datasets from one brand to another, the differences were no longer significant, with CV's of 2.2 and 11.7%, log-transformed and raw data, respectively.

Conclusion

Although activity monitors predict PA on the same scale (counts/min), the results between these two brands are not directly comparable. However, the data are comparable if a conversion equation is applied, with better results for log-transformed data.

Evaluation of a portable device to measure daily energy expenditure in free-living adults

BACKGROUND

Increasing daily energy expenditure (EE) plays an important role in the prevention or treatment of several lifestyle-related diseases; however, its measurement remains problematic.

OBJECTIVE

The objective was to evaluate a portable armband device for measuring daily and physical activity EE compared with doubly labeled water (DLW) in free-living individuals.

DESIGN

Daily EE and physical activity EE were measured in 45 subjects over a 10-d period simultaneously with 2 techniques: a portable armband and DLW. Resting metabolic rate was measured by indirect calorimetry, and the thermic effect of a meal was estimated (10% of daily EE). Physical activity EE was obtained by subtracting the values for resting metabolic rate and thermic effect of a meal measured with DLW from those measured with the armband. Body composition was measured with dual-energy X-ray absorptiometry. Concordance between measures was evaluated by intraclass correlation, SEE, regression analysis, and Bland-Altman plots.

RESULTS

Mean estimated daily EE measured with the armband was 117 kcal/d lower (2375 +/- 366 kcal/d) than that measured with DLW (2492 +/- 444 kcal/d; P < 0.01). Despite this group difference, individual comparisons between the armband and DLW were close, as evidenced by an intraclass correlation of 0.81 (P < 0.01).

CONCLUSIONS

The portable armband shows reasonable concordance with DLW for measuring daily EE in free-living adults. The armband may therefore be useful to estimate daily EE.